Zhong, W. — Page 4 | Search bioRxiv

bioRxiv2018

SMUT: multi-SNP Mediation intersection-Union Test

Tens of thousands of reproducibly identified GWAS (Genome-Wide Association Studies) variants, with the vast majority falling in non-coding regions resulting in no eventual protein products, call urgently for mechanistic interpretations. Although numerous methods exist, there are few, if any methods, for simultaneously testing the mediation effects of multiple correlated SNPs via some mediator (for example, the expression of a gene in the neighborhood) on phenotypic outcome. We propose SMUT, multi-SNP Mediation intersection-Union Test to fill in this methodological gap. Our extensive simulations demonstrate the validity of SMUT as well as substantial, up to 92%, power gains over alternative methods. In addition, SMUT confirmed known mediators in a real dataset of Finns for plasma adiponectin level, which were missed by many alternative methods. We believe SMUT will become a useful tool to generate mechanistic hypotheses underlying GWAS variants, facilitating functional follow-up. The R package SMUT is publicly available from CRAN at https://CRAN.R-project.org/package=SMUT.

genetics↗

bioRxiv2017

The Early Diagnosis in Lung Cancer by the Detection of Circulating Tumor DNA

BackgroundRemarkable advances for clinical diagnosis and treatment in cancers including lung cancer involve cell-free circulating tumor DNA (ctDNA) detection through next generation sequencing. However, before the sensitivity and specificity of ctDNA detection can be widely recognized, the consistency of mutations in tumor tissue and ctDNA should be evaluated. The urgency of this consistency is extremely obvious in lung cancer to which great attention has been paid to in liquid biopsy field.\n\nMethodsWe have developed an approach named systematic error correction sequencing (Sec-Seq) to improve the evaluation of sequence alterations in circulating cell-free DNA. Averagely 10 ml preoperative blood samples were collected from 30 patients containing pulmonary space occupying pathological changes by traditional clinic diagnosis. cfDNA from plasma, genomic DNA from white blood cells, and genomic DNA from solid tumor of above patients were extracted and constructed as libraries for each sample before subjected to sequencing by a panel contains 50 cancer-associated genes encompassing 29 kb by custom probe hybridization capture with average depth >40000, 7000, or 6300 folds respectively.\n\nResultsDetection limit for mutant allele frequency in our study was 0.1%. The sequencing results were analyzed by bioinformatic expertise based on our previous studies on the baseline mutation profiling of circulating cell-free DNA and the clinicopathological data of these patients. Among all the lung cancer patients, 78% patients were predicted as positive by ctDNA sequencing when the shreshold was defined as at least one of the hotspot mutations detected in the blood (ctDNA) was also detected in tumor tissue. Pneumonia and pulmonary tuberculosis were detected as negative according to the above standard. When evaluating all hotspots in driver genes in the panel, 24% mutations detected in tumor tissue (tDNA) were also detected in patients blood (ctDNA). When evaluating all genetic variations in the panel, including all the driver genes and passenger genes, 28% detected in tumor tissue (tDNA) were also detected in patients blood (ctDNA). Positive detection rates of plasma ctDNA in stage I lung cancer patients is 85%, compared with 17% of tumor biomarkers.\n\nConclusionWe demonstrated the importance of sequencing both circulating cell-free DNA and genomic DNA in tumor tissue for ctDNA detection in lung cancer currently. We also determined and confirmed the consistency of ctDNA and tumor tissue through NGS according to the criteria explored in our studies. Our strategy can initially distinguish the lung cancer from benign lesions of lung. Our work shows that the consistency will be benefited from the optimization in sensitivity and specificity in ctDNA detection.

cancer biology↗